Triple

T22789374
Position Surface form Disambiguated ID Type / Status
Subject Marsberg E564065 entity
Predicate locatedIn P40 FINISHED
Object eastern Sauerland NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: eastern Sauerland | Statement: [Marsberg, locatedIn, eastern Sauerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: eastern Sauerland
Context triple: [Marsberg, locatedIn, eastern Sauerland]
  • A. Sauerland chosen
    Sauerland is a hilly, forested region in western Germany known for its reservoirs, outdoor recreation, and winter sports areas.
  • B. Weserbergland
    Weserbergland is a hilly, forested region in central Germany known for its picturesque landscapes along the Weser River and numerous historic towns.
  • C. eastern Brandenburg
    Eastern Brandenburg is a region in the German federal state of Brandenburg, bordering Poland and encompassing cities such as Frankfurt (Oder).
  • D. Calenberg region
    The Calenberg region is a historical area in what is now Lower Saxony, Germany, that formed the core landholding of the House of Hanover and the former Principality of Calenberg.
  • E. Saale-Holzland region
    The Saale-Holzland region is a rural district in the German state of Thuringia, known for its Saale River landscapes, forests, and small historic towns.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c3488708190812f7d2edac92184 completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:29 p.m.